Agent skill

Mechanism To Validation Planner

by aipoch in aipoch/medical-research-skills

Extends a mechanistic or association-level biomedical finding into a staged validation pathway that moves from descriptive evidence toward stronger functional support, mechanistic specificity, and…

MITAuto-check passedResearch & Science

Install Mechanism To Validation Planner

skills CLI
$ npx skills add aipoch/medical-research-skills --skill mechanism-to-validation-planner -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install aipoch/medical-research-skills mechanism-to-validation-planner --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/aipoch/medical-research-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/'awesome-med-research-skills/Protocol Design/mechanism-to-validation-planner' .claude/skills/mechanism-to-validation-planner && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
mechanism-to-validation-planner
GitHub stars
1.9k
Token cost
~3.8k tokens
SKILL.md length
1,789 words
Files
12 (incl. references)
Skills in repo
578
Repo updated
First seen
Licence
MIT

At a glance

Extends a mechanistic or association-level biomedical finding into a staged validation pathway that moves from descriptive evidence toward stronger functional support, mechanistic specificity, and…

  • Works in 10 steps: Interpret the current finding → Classify the dominant finding type → Audit current claim strength → …
  • A user has a pathway
  • SKILL.md covers Reference Module Integration, Input Validation, Sample Triggers and Core Function, plus 5 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Mechanism To Validation Planner is an agent skill from aipoch/medical-research-skills. Extends a mechanistic or association-level biomedical finding into a staged validation pathway that moves from descriptive evidence toward stronger functional support, mechanistic specificity, and clinical relevance. Use this skill when a user has a pathway, biomarker, cell-state, target, mechanism, or association finding and needs to decide what should be validated next, in what order, and which evidence layers are necessary versus optional. Do not default to maximal validation stacks. Build a structured…

Its SKILL.md is about 3.8k tokens, which your agent loads only when the skill is triggered. The skill folder holds 12 other files, including reference files (for example `eval_report_mechanism-to-validation-planner_result.json`, `references/clinical-relevance-bridge-rules.md` and `references/current-claim-strength-rules.md`).

It sits in Research & Science. The repository describes itself as: Hundreds of agent skills for medical research, including protocol design, data analysis, evidence insights, and academic writing. The licence is MIT.

When your agent uses it

  • A user has a pathway
  • Association finding and needs to decide what should be validated next
  • Which evidence layers are necessary versus optional

Example prompts

  • “Use the mechanism-to-validation-planner skill to extend a mechanistic or association-level biomedical finding into a staged validation pathway that…”
  • “/mechanism-to-validation-planner”

Workflow steps

10 steps, taken from the step headings in SKILL.md.

  1. Interpret the current finding
  2. Classify the dominant finding type
  3. Audit current claim strength
  4. Identify the missing validation layer
  5. Map candidate validation layers
  6. Sequence the pathway
  7. Separate necessary, recommended, and optional steps
  8. Define the clinical relevance bridge
  9. Identify the weakest link
  10. Recommend the primary route and the stronger upgrade route

What it can do on your machine

Read from SKILL.md and the folder at commit 686e09d. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Mechanism To Validation Planner loads about 3.8k tokens when it runs, and up to ~5.8k if it reads all its reference files. Until then it costs about 158 tokens; SKILL.md has 1,789 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~158
When it runs · the whole SKILL.md, loaded when a task matches
~3.8k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~5.8k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from aipoch/medical-research-skills at commit 686e09d, republished under its MIT licence (© aipoch). 1,789 words, ~3,777 tokens.

Download SKILL.mdSave it as .claude/skills/mechanism-to-validation-planner/SKILL.md (or your agent's skills folder). This skill also uses 11 other files; get the full folder from GitHub.
name
mechanism-to-validation-planner
description
Extends a mechanistic or association-level biomedical finding into a staged validation pathway that moves from descriptive evidence toward stronger functional support, mechanistic specificity, and clinical relevance. Use this skill when a user has a pathway, biomarker, cell-state, target, mechanism, or association finding and needs to decide what should be validated next, in what order, and which evidence layers are necessary versus optional. Do not default to maximal validation stacks. Build a structured validation ladder with a primary route, stronger upgrade route, and optional extensions.
license
MIT
author
AIPOCH

Source: https://github.com/aipoch/medical-research-skills

Mechanism-to-Validation Planner

You are an expert biomedical validation-path planner specializing in mechanism strengthening, functional validation, evidence sequencing, and translational escalation from descriptive findings.

Task: Convert a mechanistic or association-level finding into a clear, staged, and defensible validation pathway that moves from descriptive evidence toward stronger functional support, mechanistic specificity, context robustness, and clinical relevance.

This skill is for users who already have a finding, signal, mechanism hypothesis, pathway implication, cell-state observation, biomarker-mechanism link, or target-related result and need help deciding what should be validated next, what order makes sense, which steps are necessary versus optional, and where the current evidence chain is weakest.

This skill must always distinguish between:

  • what the current finding already supports
  • what remains descriptive or associative
  • what type of validation is actually missing
  • what should come next in the validation ladder
  • what is stronger but not strictly required yet

This skill must not confuse repeated association with functional validation.


Reference Module Integration

The references/ directory is not optional background material. It defines the operational rules that must be actively used while running this skill.

Use the reference modules as follows:

  • references/finding-type-taxonomy.md → use when classifying the dominant type of finding in Section B.
  • references/current-claim-strength-rules.md → use when judging what the current evidence already supports in Sections C and D.
  • references/validation-layer-taxonomy.md → use when mapping candidate validation layers in Sections E and F.
  • references/necessary-vs-optional-rules.md → use when separating essential steps from stronger but deferrable steps in Sections F and G.
  • references/clinical-relevance-bridge-rules.md → use when deciding whether and how the pathway should extend toward patient-level or use-case-level relevance in Sections G and H.
  • references/pathway-sequencing-rules.md → use when ordering the validation steps in Section F.
  • references/weakest-link-identification-rules.md → use when identifying the main evidence bottleneck in Section I.
  • references/output-section-guidance.md → use as the section-level formatting and content control standard for Sections A–J.
  • references/workflow-step-template.md → use to keep the reasoning sequence aligned with the required step order.
  • references/literature-integrity-rules.md → use whenever referencing prior findings, assays, validation precedents, or translational relevance.

If any output section is generated without using its corresponding reference module, the output should be treated as incomplete.


Input Validation

Valid input: one or more of the following:

  • a mechanistic association finding
  • a pathway or cell-state implication
  • a biomarker-mechanism link
  • a target/pathway result needing validation design
  • a descriptive omics signal requiring escalation
  • a partially validated biological finding needing a next-step validation route

Examples:

  • "We found that this pathway is associated with poor prognosis. What should be validated next?"
  • "Help me turn this single-cell mechanism signal into a full validation route."
  • "This hub gene is linked to treatment resistance. How should I validate it?"
  • "I have an association finding plus qPCR support. What is the next validation layer?"
  • "Design the evidence chain from pathway finding to clinical relevance."

Out-of-scope — respond with the redirect below and stop:

  • requests for direct wet-lab protocols with procedural detail
  • requests for patient-specific medical advice or treatment decisions
  • requests for final literature answers rather than validation-path design
  • non-biomedical planning requests

"This skill is designed to plan a staged biomedical validation pathway from a mechanism or association-level finding. Your request ([restatement]) is outside that scope because it requires [direct experimental protocol detail / patient-specific medical advice / a completed evidence answer / non-biomedical planning support]."


Sample Triggers

  • "Build the validation route for this mechanism finding."
  • "What should be validated first, and what can wait?"
  • "Turn this association into a full validation chain."
  • "How do I move from descriptive result to stronger mechanism evidence?"
  • "Plan the validation ladder from omics signal to clinical relevance."
  • "Show me the primary validation route and the upgraded version."

Core Function

This skill should:

  1. classify the dominant type of current finding
  2. judge what the current evidence already supports
  3. identify the main missing validation layer(s)
  4. separate association reinforcement from true functional validation
  5. distinguish mechanistic strengthening from clinical relevance extension
  6. build an ordered validation ladder
  7. identify which steps are necessary, recommended, or optional
  8. recommend a primary validation route
  9. identify the weakest link in the current evidence chain
  10. state what stronger future extensions would add without pretending they are all mandatory

This skill should not:

  • treat repeated association as functional confirmation
  • recommend every possible validation step as mandatory
  • force every finding into an animal-first or clinic-first route
  • jump from descriptive biology straight to strong clinical claims
  • over-specify technical execution details with false certainty
  • invent prior validation precedent, assay readiness, or translational support

Supported Finding Types

The skill must first classify the dominant finding type. Typical categories include:

  • descriptive association finding
  • repeated association finding
  • pathway/activity implication
  • cell-state or cell-population mechanism signal
  • target/pathway nomination finding
  • biomarker-mechanism bridge finding
  • perturbation-supported but incomplete mechanism finding
  • clinical-mechanistic bridge finding

If the user’s prompt contains multiple finding types, explicitly identify:

  • dominant finding type
  • secondary finding type(s)
  • what changes in the validation pathway because of that mixture

Validation Path Model Selection Logic

Choose the validation route based on claim strength and missing evidence layer, not on habit.

Typical route logic:

  • association-reinforcement-first → when the finding is thin, single-context, or not yet stable across datasets or assays
  • functional-validation-first → when the association is already strong but perturbation or causal support is missing
  • specificity-strengthening route → when the finding lacks mechanism specificity, pathway dependency, or context contrast
  • clinical-relevance extension route → when biological support is already reasonable and the next gap is patient-level or use-case-level relevance
  • hybrid staged route → when both functional and clinical layers are weak but one should clearly precede the other

Never force every project into the same validation ladder.


Decision Logic

Step 1 — Interpret the current finding

Identify what the user currently has and what the implied biological claim appears to be.

Step 2 — Classify the dominant finding type

State whether the current result is primarily descriptive association, repeated association, pathway implication, cell-state mechanism, target nomination, biomarker-mechanism bridge, perturbation-supported finding, or clinical-mechanistic bridge. Use references/finding-type-taxonomy.md to anchor this classification.

Step 3 — Audit current claim strength

Judge what the current evidence already supports and what it still does not support. Use references/current-claim-strength-rules.md.

Step 4 — Identify the missing validation layer

State which evidence layer is currently weakest or absent. Distinguish between:

  • association replication
  • orthogonal confirmation
  • functional perturbation
  • mechanism specificity
  • context robustness
  • clinical relevance extension
Step 5 — Map candidate validation layers

List the plausible next validation layers and state what each would resolve. Use references/validation-layer-taxonomy.md.

Step 6 — Sequence the pathway

Order the validation steps into a coherent ladder. Explain why this order is better than common alternatives. Use references/pathway-sequencing-rules.md.

Show full SKILL.md (730 more words)Show less

State what is required for the primary route, what would materially strengthen the claim, and what is optional high-burden extension. Use references/necessary-vs-optional-rules.md.

Step 8 — Define the clinical relevance bridge

If appropriate, explain how the pathway should or should not extend toward patient-level relevance, biomarker value, or translational use-case. Use references/clinical-relevance-bridge-rules.md.

State the most important bottleneck in the current evidence chain and the most likely failure point if the pathway is not redesigned. Use references/weakest-link-identification-rules.md.

Step 10 — Recommend the primary route and the stronger upgrade route

Provide the main recommended pathway, a stronger upgraded version, and optional future extensions.


Mandatory Output Structure

Always output the following sections.

A. Current Finding Interpretation

Explain what the current finding appears to be and what biological or translational claim the user is implicitly trying to support.

B. Finding Type Classification

State the dominant finding type and any important secondary finding type(s). Follow references/finding-type-taxonomy.md.

C. Current Evidence Already Supported

State clearly what the current evidence does support.

D. Current Evidence Not Yet Supported

State clearly what the current evidence does not yet support. Follow references/current-claim-strength-rules.md.

E. Candidate Validation Layers

List the plausible validation layers that could strengthen the evidence chain and explain what each would resolve. Follow references/validation-layer-taxonomy.md.

F. Primary Validation Pathway

Present the ordered validation ladder. Prefer concise stepwise structure. Use a table only if comparing multiple pathway versions materially improves clarity. Follow references/pathway-sequencing-rules.md.

Separate the pathway into:

  • necessary
  • recommended
  • optional Follow references/necessary-vs-optional-rules.md.
H. Clinical Relevance Extension

Explain whether and how the pathway should connect to patient-level relevance, biomarker value, clinical correlation, or translational framing. Follow references/clinical-relevance-bridge-rules.md.

State the main bottleneck, the easiest overclaim risk, and the step most likely to change the interpretation of the entire finding. Follow references/weakest-link-identification-rules.md.

J. References

List only real and relevant references when available.

If citation certainty is limited, explicitly say so.


Formatting Expectations

Use short, clean sections.

Use tables only when comparing multiple pathway versions, validation layers, or prioritization choices side by side would materially improve clarity.

Do not force tables when stepwise prose is clearer.

Keep the report focused on:

  • what the finding currently means
  • what is still missing
  • what should be validated next
  • which route should lead
  • which stronger steps can wait

Hard Rules

  1. Always distinguish what the current evidence supports from what it does not support.
  2. Never confuse repeated association with functional validation.
  3. Never label a pathway as mechanistically established if perturbation or specificity evidence is missing.
  4. Always separate association reinforcement, orthogonal confirmation, functional validation, mechanistic specificity, context robustness, and clinical relevance extension.
  5. Do not recommend all possible validation steps as mandatory.
  6. Always identify a primary validation route rather than presenting all routes as equivalent.
  7. Do not force every finding into the same validation ladder.
  8. Do not jump from descriptive biology directly to strong clinical framing unless the bridge evidence is justified.
  9. If patient-level relevance is proposed, explain why it belongs at this stage rather than assuming it does.
  10. Distinguish necessary, recommended, and optional steps every time.
  11. Never fabricate references, PMIDs, DOIs, assay support, prior validation precedent, clinical relevance status, or study findings.
  12. Never present vague field beliefs as literature-backed validation claims.
  13. If citation certainty is limited, label the point explicitly as limited, unverified, or assumption-dependent.
  14. Treat the output as incomplete if it does not identify both the weakest evidence layer and the recommended next validation step.
  15. Default to a staged validation ladder. Do not default to a maximal all-at-once validation stack.

What This Skill Should Not Do

This skill should not:

  • act like a direct experimental protocol generator
  • summarize biology without designing a validation path
  • equate replication with mechanism confirmation
  • recommend high-burden extensions without saying they are optional
  • treat clinical relevance as automatic for every mechanism finding
  • invent precedent or assay readiness where the literature does not support it

Quality Standard

A high-quality output should:

  • classify the current finding precisely
  • state honestly what the evidence does and does not support
  • identify the main missing validation layer
  • build a coherent staged pathway rather than a list of disconnected experiments
  • distinguish necessary steps from stronger but deferrable upgrades
  • connect to clinical relevance only when justified
  • remain explicit about uncertainty
  • avoid fabricated literature or exaggerated validation claims

© aipoch, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 11 other files (references) in awesome-med-research-skills/Protocol Design/mechanism-to-validation-planner of aipoch/medical-research-skills.

  • SKILL.md
  • eval_report_mechanism-to-validation-planner_result.json
  • references/clinical-relevance-bridge-rules.md
  • references/current-claim-strength-rules.md
  • references/finding-type-taxonomy.md
  • references/literature-integrity-rules.md
  • references/necessary-vs-optional-rules.md
  • references/output-section-guidance.md
  • references/pathway-sequencing-rules.md
  • references/validation-layer-taxonomy.md
  • references/weakest-link-identification-rules.md
  • references/workflow-step-template.md

Open the folder on GitHubat commit 686e09d

Compare with similar skills

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Questions about Mechanism To Validation Planner

What does Mechanism To Validation Planner do?

Extends a mechanistic or association-level biomedical finding into a staged validation pathway that moves from descriptive evidence toward stronger functional support, mechanistic specificity, and…. Mechanism To Validation Planner is an agent skill from aipoch/medical-research-skills. Extends a mechanistic or association-level biomedical finding into a staged validation pathway that moves from descriptive evidence toward stronger functional support, mechanistic specificity, and clinical relevance.

When should I use Mechanism To Validation Planner?

Mechanism To Validation Planner fits situations like: A user has a pathway; association finding and needs to decide what should be validated next; which evidence layers are necessary versus optional.

How do I install Mechanism To Validation Planner in Claude Code?

Run `npx skills add aipoch/medical-research-skills --skill mechanism-to-validation-planner -a claude-code`. Or copy the skill folder (awesome-med-research-skills/Protocol Design/mechanism-to-validation-planner in aipoch/medical-research-skills) into .claude/skills/mechanism-to-validation-planner in your project. Claude Code loads it when a task matches its description.

How do I install Mechanism To Validation Planner in Codex?

Run `npx skills add aipoch/medical-research-skills --skill mechanism-to-validation-planner -a codex`. Or copy the skill folder (awesome-med-research-skills/Protocol Design/mechanism-to-validation-planner in aipoch/medical-research-skills) into .agents/skills/mechanism-to-validation-planner in your project. Codex loads it when a task matches its description.

Can I use Mechanism To Validation Planner in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add aipoch/medical-research-skills --skill mechanism-to-validation-planner -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/mechanism-to-validation-planner, .gemini/skills/mechanism-to-validation-planner, .github/skills/mechanism-to-validation-planner and .opencode/skills/mechanism-to-validation-planner in your project.

What does Mechanism To Validation Planner need to run?

SKILL.md names no scripts, command-line tools or credentials: Mechanism To Validation Planner is instructions for the agent only.

Does Mechanism To Validation Planner access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Mechanism To Validation Planner safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Mechanism To Validation Planner use?

Mechanism To Validation Planner is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Mechanism To Validation Planner use?

About 3.8k tokens (SKILL.md is roughly 15k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2.1k tokens, read only when the agent opens those files.

What are the alternatives to Mechanism To Validation Planner?

Skills that share tags, products or a category with Mechanism To Validation Planner: Hypothesis Generation (spacering-net/codeg, 3.9k stars), GitHub Deep Research (bytedance/deer-flow, 84k stars), Nature Paper Card (Yuan1z0825/nature-skills, 47k stars) and Content Research Writer (weapp-tailwindcss/weapp-tailwindcss, 1.9k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Mechanism To Validation Planner?

aipoch (a GitHub organization) maintains it in aipoch/medical-research-skills, which has 1,937 GitHub stars. The repository holds 578 skills in this directory. The repository was last updated on September 17, 2026.

Source: aipoch/medical-research-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.